diff options
Diffstat (limited to 'tensorflow/contrib/metrics/python/ops/metric_ops.py')
| -rw-r--r-- | tensorflow/contrib/metrics/python/ops/metric_ops.py | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/tensorflow/contrib/metrics/python/ops/metric_ops.py b/tensorflow/contrib/metrics/python/ops/metric_ops.py index d7c73c8f99..91939b5bf2 100644 --- a/tensorflow/contrib/metrics/python/ops/metric_ops.py +++ b/tensorflow/contrib/metrics/python/ops/metric_ops.py @@ -3222,11 +3222,11 @@ def streaming_covariance(predictions, # batch_mean_prediction is E[x_B] in the update equation batch_mean_prediction = math_ops.div_no_nan( math_ops.reduce_sum(weighted_predictions), - math_ops.maximum(batch_count, 0), + batch_count, name='batch_mean_prediction') delta_mean_prediction = math_ops.div_no_nan( (batch_mean_prediction - mean_prediction) * batch_count, - math_ops.maximum(update_count, 0), + update_count, name='delta_mean_prediction') update_mean_prediction = state_ops.assign_add(mean_prediction, delta_mean_prediction) @@ -3236,11 +3236,11 @@ def streaming_covariance(predictions, # batch_mean_label is E[y_B] in the update equation batch_mean_label = math_ops.div_no_nan( math_ops.reduce_sum(weighted_labels), - math_ops.maximum(batch_count, 0), + batch_count, name='batch_mean_label') delta_mean_label = math_ops.div_no_nan( (batch_mean_label - mean_label) * batch_count, - math_ops.maximum(update_count, 0), + update_count, name='delta_mean_label') update_mean_label = state_ops.assign_add(mean_label, delta_mean_label) # prev_mean_label is E[y_A] in the update equation |